Ito process: Difference between revisions
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== Description of the Ito Processes == | == Description of the Ito Processes == | ||
Let <math>(\Omega, F, \mathbb{F}, \mathbb{P})</math> be a probability space with a filtration <math>\mathbb{F}=(F_t)_{t\geq 0}</math> that we consider as complete (that is to say, all sets which measure is | Let <math>(\Omega, F, \mathbb{F}, \mathbb{P})</math> be a probability space with a filtration <math>\mathbb{F}=(F_t)_{t\geq 0}</math> that we consider as complete (that is to say, all sets which measure is equal to zero are contained in <math>F_0</math> | ||
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<math>X_t = X_0 + \int_0^t K_s\mathrm{ds} + \sum_{j=1}^d\int_0^t H^j_s | <math>X_t = X_0 + \int_0^t K_s\mathrm{ds} + \sum_{j=1}^d\int_0^t H^j_s\times\mathrm{dB}_s^j</math> | ||
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* <math>(K_t)_{t\geq 0}</math> is a progressively measurable process such as <math>\forall t\geq 0,\ \int_0^t|K_s|\textrm{ds}<+\infty</math> almost surely. | * <math>(K_t)_{t\geq 0}</math> is a progressively measurable process such as <math>\forall t\geq 0,\ \int_0^t|K_s|\textrm{ds}<+\infty</math> almost surely. | ||
* <math>(H^i_t)_{t\geq 0,\ i\in[1\dots d]}</math> is progressively measurable and such as <math>\forall i\in [1\dots d],\ \forall t\geq 0,\ \int_0^t(H_s^i)^2\mathrm(ds)<+\infty</math> almost surely. | * <math>(H^i_t)_{t\geq 0,\ i\in[1\dots d]}</math> is progressively measurable and such as <math>\forall i\in [1\dots d],\ \forall t\geq 0,\ \int_0^t(H_s^i)^2\mathrm(ds)<+\infty</math> almost surely. | ||
We note then <math>I</math> the set of Ito Processes. We can also note that all Ito Processes are continuous and adapted to the filtration <math>\textbb{F}</math>. We can also write the Ito Process under a 'differential form' : | |||
<math>dX_t = K_tdt + \sum_{j=1}^dH_t^jdB_t^j</math> | |||
Using the fact that the brownian part is a [[local martingal]], and that all continuous local martingal with finite variations equal to zero in zero is indistinguishible of the null process, we can show that this decomposition is unique (except for indistinguishibility) for each Ito Process. | |||
Revision as of 14:25, 28 December 2008
An Ito Process is a type of stochastic process described by Japanese mathematician Kiyoshi Ito, which can be written as the sum of the integral of a process over time and of another process over a Brownian Motion.
Those processes are the base of Stochastic Integration, and are therefore widely used in Financial Mathematics and Stochastic Calculus.
Description of the Ito Processes
Let be a probability space with a filtration that we consider as complete (that is to say, all sets which measure is equal to zero are contained in
Let also be a d-dimensional - Standard Brownian Motion.
Then we call Ito Process all process that can be written like :
Where :
- is measurable
- is a progressively measurable process such as almost surely.
- is progressively measurable and such as almost surely.
We note then the set of Ito Processes. We can also note that all Ito Processes are continuous and adapted to the filtration Failed to parse (unknown function "\textbb"): {\displaystyle \textbb{F}}
. We can also write the Ito Process under a 'differential form' :
Using the fact that the brownian part is a local martingal, and that all continuous local martingal with finite variations equal to zero in zero is indistinguishible of the null process, we can show that this decomposition is unique (except for indistinguishibility) for each Ito Process.